ROBUSTNESS OF NON-PARAMETRIC MEASUREMENT OF EFFICIENCY AND RISK AVERSION

This paper examines the performance of a risk-adjusted non-parametric approach to measuring efficiency and risk aversion. Prior work is extended to the case where agent behavior is motivated by expected utility maximization. Results indicate the approach significantly outperforms traditional efficiency measurement methods when applied to risk averse agents.Risk and Uncertainty,

Efficacy of DNA Sampling to Monitor Population Abundance of Black Bears in the Southern Appalachians

The American black bear (Ursus americanus) in the southern Appalachians has been the subject of intensive research. In particular, the focus has been on population monitoring using livecapture, bait stations, harvest records, and radio-active feces tagging. Genetic (DNA) sampling for mark-recapture is an emerging technique for estimating population abundance, but the efficacy of various sampling regimes for estimating populations of different densities has not been established. I conducted a pilot study to determine whether genetic sampling for population estimation is feasible to monitor black bear abundance in the southern Appalachians and to develop appropriate sampling regimes to obtain desired levels of precision. Specifically, I investigated how the density of sampling sites, number of samples analyzed, and sampling duration affect the accuracy and precision of population estimates. Research was conducted for 10 weeks from 9 June to 15 August 2003 on 2 study areas: a high-density black bear population in a portion of Great Smoky Mountains National Park (the national park study area), and a lower-density black bear population on national forest lands in North Carolina, South Carolina, and Georgia (the national forest study area). DNA was extracted from hair collected from baited barbed-wire enclosures. The average number of hair-capture sites within a typical female home range was 2.71 and 2.48 for the national park and national forest study areas, respectively. Twenty-five hair samples/week were randomly chosen for DNA analysis. Individuals were identified by their unique genetic profile obtained from 9 to 10 microsatellite loci. I identified 129 and 60 individual bears in the national park and national forest study area, respectively. Reductions in site density, subsample intensity, or sampling duration tended to produce low, heterogeneous capture probabilities, resulting in unreliable population estimates. Sample sizes and capture probabilities were smaller and population estimates decreased as the 3 factors were reduced. Those trends were particularly apparent for the national park study area, where capture probabilities were particularly low. The combination of small sample sizes and heterogeneous capture probabilities likely were a result of an insufficient number of hair-capture sites and number of analyzed hair samples relative to the size of the sampled population. Increasing these 2 factors likely would increase sample sizes and capture probabilities and reduce heterogeneity of capture probabilities present in the data. However, increasing the number of analyzed samples also would increase costs. Because pooled sampling periods increased capture probabilities, I selected a pooled configuration for population estimation that yielded relatively high capture probabilities (3 periods comprised of 3 weeks each). I used the heterogeneity model Mh Chao, which produced an estimate of 292 bears (95% CI = 214–435) for the national park study area and 98 bears (95% CI = 76–149) for the national forest study area (density = 1.83 bears/km2and 0.30 bears/km2, respectively). My results indicate that effective implementation for black bear population estimation requires careful consideration of study design. Capture probabilities of ≥20% are required to minimize bias, and this would be best achieved by analyzing more subsamples from a greater density of hair-capture sites, particularly in high-density populations. I recommend ≥4 hair-capture sites/female home range to reduce heterogeneity and a sampling duration of 6–8 weeks to reduce violation of geographic closure. In the national forest study area reasonably unbiased population estimates were achieved with 20 hair samples/week, but as many as 40 hair samples/week may be required to produce reliable estimates for the national park study area

FACTORS DETERMINING FSA GUARANTEED LOAN LOSS CLAIM ACTIVITY IN THE U.S. FOR 1990-1997

The study identifies farm operator and economic characteristics explaining variation in FSA guaranteed loan loss claims rates. Regression models using state-level data are estimated. Debt-to-asset ratios, interest rates, off-farm income and bank loan-to-asset ratios explain FO loss rates. Farm size and bank loan-to-asset ratios are important to OL loss rates.Agricultural Finance,

Factors Determining the Use of Guaranteed Loans by U.S. Commercial Banks

Financial Economics,